CVPR 2019 Workshop and Challenge:

Automated Analysis of Marine Video for Environmental Monitoring

Call for Papers

Manual annotation of imagery is the largest bottleneck to studying many important problems in the underwater domain. This workshop will convene experts and researchers from both marine science and computer vision communities to learn about the challenges, current work, and opportunities in marine imagery analysis. The workshop is currently accepting papers involving computer vision applied to aquatic environmental monitoring, including:

  • Types of data (e.g. number, size, species classification) resource managers need to extract from video
  • Animal detection and tracking in video
  • Animal species classification
  • Segmentation in high-density populations (e.g. schooling fish, seals hauled out on beaches)
  • Animal behavior analysis and classification
  • 3D reconstruction and volumetric assessment of animals
  • Normalcy modeling and anomaly detection
  • Aquatic plant and coral classification
  • Habitat and substrate classification
  • Underwater SLAM
  • Other imaging sensing modalities (sonar, lidar, hyperspectral)
  • Physics-based vision as it pertains to marine imaging, e.g. refraction at the surface and fluorescence
  • Methods that operate in far-field, low-contrast conditions
  • Image and video enhancement for underwater conditions including high turbidity
  • Interactive methods including on-the-fly model training

Please see our CMT page for paper submissions. The page limit is 8 pages, not including references, following the standard CVPR format. Each paper will be reviewed by at least two members of the program committee.

Important Dates

  • April 23 (11:59 PM EST): Submissions due for both standard track and data-challenge papers
  • May 10: Decision to authors
  • May 17: Camera-ready submissions due
  • June 17: (full day) workshop at CVPR 2019

Data Challenge

We provide annotated videos from the National Oceanic and Atmospheric Administration (NOAA) that show many species of fish, shellfish, underwater plants, and other biota, and we are looking for algorithms that will achieve the highest detection and classification accuracy of organisms in the provided videos! Please see the data challenge for details. Submissions will be evaluated against a test sequence withheld until the end of the competition, and the winners invited to the conference. Please note that you do not have to submit a paper to the workshop to participate in the data challenge.

Related and Previous Workshops

  • ICCV 2013, the Underwater Vision Workshop
  • IEEE WACV 2015, 2016, and 2017 Automated Analysis of Video Data for Wildlife Surveillance (AVDWS)
  • ICCV 2017, The First Workshop on Visual Wildlife Monitoring
  • CVPR 2018, Automated Analysis of Marine Video for Environmental Monitoring Workshop